Methods in Biostatistics I OpenCourseWare: Free Online Introductory Course in Biostatistics by Johns Hopkins University
Are you looking for free online materials to help you study for a biostatistics class? Look no further than Johns Hopkins University's OpenCourseWare class, 'Methods in Biostatistics I.' Intended for students with a background in college-level linear algebra, calculus and science, this undergraduate-level course helps students to grasp the fundamental principles of applied biostatistics and statistical inference. This free online class is intended for students studying Mathematics, Biology or Statistics.
Methods in Biostatistics I: Course Specifics
| Degree Level | Free | Audio | Video | Downloads |
|---|---|---|---|---|
| Undergraduate | Yes | No | No | Yes |
| Lectures/Notes | Study Materials | Tests/Quizzes |
|---|---|---|
| Yes | Yes | No |
Methods in Biostatistics I: Course Details
'Methods in Biostatistics I' is a free OpenCourseWare class taught by Johns Hopkins University's Brian Caffo. This lecture-based course is intended for students who already have a firm grasp of college-level math, biostatistics and the quantitative sciences, but who need a refresher in certain mathematical concepts and an overview of applied statistics. Before you jump in and start studying, however, make sure that this undergraduate-level class is for you. The course materials states that the course material is too specific for students seeking a general introduction to the field of biostatistics. The course materials focus on a wide range of topics, including applied probability, the central limit theorem and hypothesis testing. Students will learn to calculate Bernoulli variance, apply Baye's rule and define, interpret and plot likelihood. By using these free online study materials students will gain a firm grasp of the basics of statistics, probability and computations, as well as how to effectively present and communicate data.
Materials for this free OpenCourseWare include 14 downloadable lectures, an annotated reading list and links to other online resources. To learn more, visit the introduction to biostatistics course page.
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